The Chinese named entity recognition (NER) task is a sub-task within the information extraction domain, where the task goal is to find, identify and classify relevant entities, such as names of people, places and organizations, from sentences given a pie
A SURVEY ON CHINESE NAMED ENTITY RECOGNITIONYaxiong Han
A Survey on Deep Learning for Named Entity Recognition命名实体识别综述 1.命名实体识别的定义 命名实体识别就是从文本中识别出特定的语法定义类型如人名、地名、组织名等内容。 2.命名实体识别的意义 命名实体识别不仅是信息抽取的一个独立工具,同时它在其他的NLP任务中也有很重要的作用。如文本理解、信息复原、自...
第一步:( Distributed Representations for Input)输入的分布式表示形式考虑了单词和字符级别的嵌入,以及结合了对特征有效的POS标签和地名词典等其他特征,其目的是字符向量化(token)。 第二步:( Context Encoder Architectures)上下文编码器将使用CNN,RNN或其他网络捕获上下文相关性,其目的是文本的特征向量。 第三步:(Tag...
2024. An adaptive multi-neural network model for named entity recognition of Chinese mechanical equipment corpus. Journal of Engineering Design ► pp. 1 ff. MA, Kai, Xinxin HU, Miao TIAN, Yongjian TAN, Shuai ZHENG, Liufeng TAO & Qinjun QIU 2024. GeoNER: Geological Named Entity R...
This survey covers fifteen years of research in the Named Entity Recognition and Classification (NERC) field, from 1991 to 2006. We report observations about languages, named entity types, domains and textual genres studied in the literature. From the start, NERC systems have been developed using...
This survey covers fifteen years of research in the Named Entity Recognition and Classification (NERC) field, from 1991 to 2006. We report observations about languages, named entity types, domains and textual genres studied in the literature. From the start, NERC systems have been developed using...
Named Entity Recognition (NER) is a sub task of Information Extraction (IE) used to identify and classify the names in any given data. Earlier studies were mostly based on hand written rules where as now-a-days Machine Learning models such as Hidden Markov Model (HMM), Maximum Entropy (Max...
E.g., Named Entity Recognition is a first-level area in our categorization because it is the focus of several surveys. Statistics We show the number of paper in each area in Figures 1-2. Figure 1: # of papers in each NLP area. Figure 2: # of papers in each ML area. Also, we ...
Deep Learning Architectures for Named Entity Recognition: A Survey Over the past few years, deep learning has turned out as a powerful machine learning technique yielding state-of-the-art performance on many domains. Recen... A Thomas,S Sangeetha - International Conference on Advanced Computing &...